Merge branch 'dev' of github.ibm.com:Maria-Irina-Nicolae/nemesis into dev

Author: Irina Nicolae

art/metrics.py

@@ -153,7 +153,7 @@ def clever_u(classifier, x, n_b, n_s, r, norm, c_init=1, pool_factor=10):
     :rtype: `float`
     """
     # Get a list of untargeted classes
-    y_pred = classifier.predict(np.array([x]), logits=False)
+    y_pred = classifier.predict(np.array([x]), logits=True)
     pred_class = np.argmax(y_pred, axis=1)[0]
     untarget_classes = [i for i in range(classifier.nb_classes) if i != pred_class]
 
@@ -192,7 +192,7 @@ def clever_t(classifier, x, target_class, n_b, n_s, r, norm, c_init=1, pool_fact
     :rtype: `float`
     """
     # Check if the targeted class is different from the predicted class
-    y_pred = classifier.predict(np.array([x]), logits=False)
+    y_pred = classifier.predict(np.array([x]), logits=True)
     pred_class = np.argmax(y_pred, axis=1)[0]
     if target_class == pred_class:
         raise ValueError("The targeted class is the predicted class")
@@ -226,7 +226,7 @@ def clever_t(classifier, x, target_class, n_b, n_s, r, norm, c_init=1, pool_fact
         sample_xs = rand_pool[np.random.choice(pool_factor * n_s, n_s)]
 
         # Compute gradients
-        grads = classifier.class_gradient(sample_xs, logits=False)
+        grads = classifier.class_gradient(sample_xs, logits=True)
         if np.isnan(grads).any():
             raise Exception("The classifier results NaN gradients")
 
@@ -239,7 +239,7 @@ def clever_t(classifier, x, target_class, n_b, n_s, r, norm, c_init=1, pool_fact
     [_, loc, _] = weibull_min.fit(-np.array(grad_norm_set), c_init, optimizer=scipy_optimizer)
 
     # Compute function value
-    values = classifier.predict(np.array([x]), logits=False)
+    values = classifier.predict(np.array([x]), logits=True)
     value = values[:, pred_class] - values[:, target_class]
 
     # Compute scores